Principal Product Manager - M365 Core Platform

The Microsoft 365 Core Platform team is hiring a Principal Product Manager to take on cross-cutting work in performance, latency, scalability, efficiency, reliability, and resource optimization across the server-side systems behind Microsoft 365 and Copilot. This is a broad role for someone who likes moving across the platform rather than holding a single area, and who is comfortable picking up high-impact work that spans teams. The focus is the infrastructure that keeps these products fast and efficient as AI workloads grow. M365 Core Platform is the foundation for the productivity experiences customers rely on, and this role shapes the capabilities that keep Microsoft 365 and Copilot performing well as they scale.

This is an AI-first product management role. You will use agents, automation, and AI-driven analysis alongside standard PM tools to read telemetry, test ideas, prototype solutions, and reach decisions faster. You will translate hard technical topics into business terms and help the team plan, prioritize, and ship with AI built into how the work gets done.

You will work across platform architecture, distributed systems, AI-powered services, and engineering teams, with strong product sense, technical depth, AI fluency, and comfort working with data. The role depends on close partnership with engineering leaders across Microsoft and carries broad visibility and influence across the company.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

- Shape platform strategy for the performance, efficiency, and scale work that matters most across Microsoft 365 and Copilot, and turn that direction into a roadmap teams can execute.

- Find and lead work focused on latency, efficiency, and platform, using AI-driven analysis of telemetry, experiments, and operational signals to catch issues early and fix them at the root.

- Use agents, automation, and AIOps to analyze data, coordinate work, and act on what you learn.

- Use AI prototyping to model tradeoffs, test scenarios, and stress-test platform investments before committing, paired with solid product and engineering judgment.

- Weigh tradeoffs and prioritize long-term platform investments with partners in other organizations.